Proceedings of the 4th International Conference on Informatization Economic Development and Management, IEDM 2024, February 23–25, 2024, Kuala Lumpur, Malaysia

Research Article

Terminal Collaborative Path Optimization of Multi-Distribution Subjects for Electric Unmanned Vehicles

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  • @INPROCEEDINGS{10.4108/eai.23-2-2024.2345955,
        author={Zifu  Fan and Zhiqiao  Sun},
        title={Terminal Collaborative Path Optimization of Multi-Distribution Subjects for Electric Unmanned Vehicles},
        proceedings={Proceedings of the 4th International Conference on Informatization Economic Development and Management, IEDM 2024, February 23--25, 2024, Kuala Lumpur, Malaysia},
        publisher={EAI},
        proceedings_a={IEDM},
        year={2024},
        month={5},
        keywords={electric unmanned vehicle logistics; multiple distribution subjects; collaborative distribution; terminal delivery; path optimization},
        doi={10.4108/eai.23-2-2024.2345955}
    }
    
  • Zifu Fan
    Zhiqiao Sun
    Year: 2024
    Terminal Collaborative Path Optimization of Multi-Distribution Subjects for Electric Unmanned Vehicles
    IEDM
    EAI
    DOI: 10.4108/eai.23-2-2024.2345955
Zifu Fan1, Zhiqiao Sun1,*
  • 1: Chongqing University of Posts and Telecommunications
*Contact email: 1015695228@qq.com

Abstract

Because the planning and design of urban logistics systems do not incorporate terminal logistics distribution into unified solutions, less consideration is given to the collaborative distribution environment of multiple distribution subjects. This oversight results in low overall efficiency and service quality of logistics distribution. Simultaneously, considering the impact of reducing energy consumption and episodic sites on logistics distribution, electric unmanned vehicles with high efficiency, low cost, and noncontact features have become the main vehicle of terminal logistics distribution. Therefore, this paper considers urban terminal distribution, constructs a multiagent collaborative distribution model with electric unmanned vehicles as the carrier, and designs an improved Tabu Search algorithm to solve the model. In simulation, our optimization model can fully realize the advantages of energy savings, emission reduction and cost reduction of electric unmanned vehicles compared to operation using the traditional single distribution and single source vehicle distribution models. The solution provided here can also reduce the promotion of terminal distribution in logistics activities and promote the green, low carbon and sustainable development in cities.